Comparative Studies And Forested Areas On Biodiversity And Land-Use Change (LUC) In Penang Island

The Global Forest Resources Assessment 2015 reported an increasing rate of privately owned forests on a global scale. However, deforestation was found to be very active in privately owned hill forest areas of Malaysia. Penang State was purposively chosen as it has been experiencing rapid and radical changes due to urban expansion over the last three decades. In this study, effect of differential management on land-use changes (LUC) and biodiversity were analysed. Analyses of land-use changes (LUC) were done by PCI Geomatica using Landsat images from 1991 to 2015 and future trends of LUC were assessed using EXCEL forecast function

Three Decades of River Bank Erosion and Accretion Appraisal Along Bank Line Shifting Trend in A Transboundary River, Teesta Floodplain of Bangladesh

As the world's largest delta, Bangladesh possesses distinctive geomorphology dominated by transboundary rivers, making it vulnerable to climatic hazards such as river erosion that causes severe loss of land and other resources. Using four Landsat imageries of 1991, 2001, 2011 and 2021 the current study analyzed the amount and trend of river erosion and accretion on the Teesta Floodplain of Bangladesh for three decades. Findings indicate that the Teesta River experiences severe bank erosion and accretion regularly, causing bank line shifting and thus significant affecting the land-use/land-cover (LULC) change of the area. Between 1991 and 2021, approximately 194 square kilometers of land were eroded, while an equivalent area of land was accreted. Approximately 1072 km2 of agricultural land was converted into other categories, with the settlement area gradually increasing. This trend of changes shows that agricultural land and water-bodies will reduce in the next two decades while barren land and settlement areas will increase. The agricultural lands and barren lands have a greater chance of being occupied by settlement areas. At the same time, crop production patterns will move to those crops that require less water due to the reduction of water-bodies. Reduced flow during the dry season and massive discharge during the monsoon from India's Gajoldoba barrage caused massive siltation and erosion. Comprehensive river management and restoration with an intergovernmental treaty or understanding between India and Bangladesh is required to resolve this crisis in the long run

Estimating growing stock volume in a Bangladesh forest site using Landsat TM and field-measured data

ABSTRACT Estimation of forest Growing Stock (GS) is important in understanding the ecological dynamics and productive capacity of forests. Instead of the traditional cost-effective and time consuming ground based measurements, satellite images are being increasingly used in estimating many forest parameters including GS. This study estimates forest GS at Khadimnagar national park, Sylhet, Bangladesh using regression relationship of vegetation indices (VIs) of Landsat Thematic Mapper (TM) image with field-measured GS. Among the VIs, NDVI (Normalized Difference Vegetation Index) was found to be the best predictor of forest GS with workable accuracy (r 2 = 0.77, P <0.000), while IRI (Infra-red Index) was the poorest estimator (r 2 = 0.38, P < 0.001). This approach could be operationally used for wider scale estimation of GS in similar forest areas of Bangladesh

Delicar: A smart deep learning based self driving product delivery car in perspective of Bangladesh

The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. The equipped camera module captures the road image and transfers it to the computer via socket server programming. The raspberry pi sends the camera image and waits for the steering angle value. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. Based upon this direction, L298 decides either forward or left or right or backwards movement. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. After that, Folium is used to depict the geographical location. Moreover, the system’s infrastructure is far too low-cost and easy to install.publishedVersio

Characteristics and potential uses of sewage sludge in the commercial capital of Bangladesh

Based on contrasting properties, sewage sludge can be co-recycled in order to take simultaneously the best profit and minimise environmental pollution. The present study was conducted to assess the physical and chemical properties of sewage sludge generated from different sources in the commercial capital of Bangladesh and on the basis of these characteristics a variety of ways had been fixed to seek out its potential uses. Presence of plant nutrients and organic matter in sufficient quantities, make sludge disposal on land an attractive option. Nitrogen has received most attention and it is normally the most abundant sludge nutrient. The other two prime nutrients phosphorus and potassium content in sewage found significantly higher than the normal soil. To inquire the possible utilisation the growth performance of one tree species was tested in an experiment using the sewage sludge and normal soil and found significant positive growth variation in sewage application compare to the normal soil.sewage sludge; potential use; waste disposal; commercial capital; tree growth; Bangladesh; environmental pollution; recycling; trees; plant nutrients; organic matter.

Preparation and Optimization of PEGylated Nano Graphene Oxide-Based Delivery System for Drugs with Different Molecular Structures Using Design of Experiment (DoE)

Graphene oxide (GO), due to its 2D planar structure and favorable physical and chemical properties, has been used in different fields including drug delivery. This study aimed to investigate the impact of different process parameters on the average size of drug-loaded PEGylated nano graphene oxide (NGO-PEG) particles using design of experiment (DoE) and the loading of drugs with different molecular structures on an NGO-PEG-based delivery system. GO was prepared from graphite, processed using a sonication method, and functionalized using PEG 6000. Acetaminophen (AMP), diclofenac (DIC), and methotrexate (MTX) were loaded onto NGO-PEG particles. Drug-loaded NGO-PEG was then characterized using dynamic light scattering (DLS), Fourier transform infrared (FTIR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), XRD. The DLS data showed that the drug-loaded NGO-PEG suspensions were in the size range of 200 nm–1.3 µm. The sonication time and the stirring rate were found to be the major process parameters which affected the average size of the drug-loaded NGO-PEG. FTIR, DSC, XRD, and SEM demonstrated that the functionalization or coating of the NGO occurred through physical interaction using PEG 6000. Methotrexate (MTX), with the highest number of aromatic rings, showed the highest loading efficiency of 95.6% compared to drugs with fewer aromatic rings (diclofenac (DIC) 70.5% and acetaminophen (AMP) 65.5%). This study suggests that GO-based nano delivery systems can be used to deliver drugs with multiple aromatic rings with a low water solubility and targeted delivery (e.g., cancer)

Preparation and Optimization of PEGylated Nano Graphene Oxide-Based Delivery System for Drugs with Different Molecular Structures Using Design of Experiment (DoE)

Graphene oxide (GO), due to its 2D planar structure and favorable physical and chemical properties, has been used in different fields including drug delivery. This study aimed to investigate the impact of different process parameters on the average size of drug-loaded PEGylated nano graphene oxide (NGO-PEG) particles using design of experiment (DoE) and the loading of drugs with different molecular structures on an NGO-PEG-based delivery system. GO was prepared from graphite, processed using a sonication method, and functionalized using PEG 6000. Acetaminophen (AMP), diclofenac (DIC), and methotrexate (MTX) were loaded onto NGO-PEG particles. Drug-loaded NGO-PEG was then characterized using dynamic light scattering (DLS), Fourier transform infrared (FTIR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), XRD. The DLS data showed that the drug-loaded NGO-PEG suspensions were in the size range of 200 nm–1.3 µm. The sonication time and the stirring rate were found to be the major process parameters which affected the average size of the drug-loaded NGO-PEG. FTIR, DSC, XRD, and SEM demonstrated that the functionalization or coating of the NGO occurred through physical interaction using PEG 6000. Methotrexate (MTX), with the highest number of aromatic rings, showed the highest loading efficiency of 95.6% compared to drugs with fewer aromatic rings (diclofenac (DIC) 70.5% and acetaminophen (AMP) 65.5%). This study suggests that GO-based nano delivery systems can be used to deliver drugs with multiple aromatic rings with a low water solubility and targeted delivery (e.g., cancer)

Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh

The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. The equipped camera module captures the road image and transfers it to the computer via socket server programming. The raspberry pi sends the camera image and waits for the steering angle value. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. Based upon this direction, L298 decides either forward or left or right or backwards movement. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. After that, Folium is used to depict the geographical location. Moreover, the system’s infrastructure is far too low-cost and easy to install

Development of Stable Liposomal Drug Delivery System of Thymoquinone and Its In Vitro Anticancer Studies Using Breast Cancer and Cervical Cancer Cell Lines

Thymoquinone, a well-known phytoconstituent derived from the seeds of Nigella sativa, exhibits unique pharmacological activities However, despite the various medicinal properties of thymoquinone, its administration in vivo remains challenging due to poor aqueous solubility, bioavailability, and stability. Therefore, an advanced drugdelivery system is required to improve the therapeutic outcome of thymoquinone by enhancing its solubility and stability in biological systems. Therefore, this study is mainly focused on preparing thymoquinone-loaded liposomes to improve its physicochemical stability in gastric media and its performance in different cancer cell line studies. Liposomes were prepared using phospholipid extracted from egg yolk. The liposomal nano preparations were evaluated in terms of hydrodynamic diameter, zeta potential, microscopic analysis, and entrapment efficiency. Cell-viability measurements were conducted using breast and cervical cancer cell lines. Optimized liposomal preparation exhibited polygonal, globule-like shape with a hydrodynamic diameter of less than 260 nm, PDI of 0.6, and zeta potential values of −23.0 mV. Solid-state characterizations performed using DSC and XRPD showed that the freeze-dried liposomal preparations were amorphous in nature. Gastric pH stability data showed no physical changes (precipitation, degradation) or significant growth in the average size of blank and thymoquinone-loaded liposomes after 24 h. Cell line studies exhibited better performance for thymoquinone-loaded liposomal drug delivery system compared with the thymoquinone-only solution; this finding can play a critical role in improving breast and cervical cancer treatment management

Complete mitochondrial genome sequence of Black Bengal goat (Capra hircus)

The Black Bengal goat (Capra hircus), is a native breed found in Bangladesh, popular due to its economic contribution. Here, we report the complete mitochondrial genome sequence of Black Bengal goat. The circular genome is 16,640 bp long, comprising of 60.89% AT content. The genome contains 37 genes, consisting of 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and a control region (D-loop)